Historically, storing data has been expensive. For that reason, companies have had to hire employees whose sole purpose was to maintain databases and delete obsolete information. Over time, storage has become increasingly inexpensive. However, the vast majority of programmers have maintained the mindset accompanying expensive storage, which has led to the sacrifice of efficiency and reliability in order to minimize the amount of data being stored. For example, programmers may write programs that only save the most recent version of any given data while deleting older versions of data. Deleting old versions of data is no longer necessary because there is no longer a significant cost associated with storing them. Although the practice of saving only the most recent version of data is functional, it also limits the manner in which application data may be stored and preserved. In some instances, it limits data from being automatically backed up at all points in time. For example, using conventional systems, data storage managers may be forced to regularly back up files and databases to preserve data. Sometimes, this includes extensive manual operations and typically still fails to preserve every instance of changed data that has taken place.
Some conventional data storage methods have attempted to store data in a cloud (remote storage sites typically accessed across a network that does not require end-user knowledge to utilize). However, such data storage methods do not enable multi-user interfacing, because different users concurrently attempting to change stored data presents data reliability problems. Furthermore, conventional storage methods typically utilize schema-based storage that requires storing the data in a particular format and structure, which limits the functionality of the storage databases that are being used. Additionally, conventional storage methods often require specific language formats that may result in incompatibility or translation needs between an application and a server.